• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.130-132
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• 2012

The use of visual media has been increased by development of contemporary society. To use these information of image, there are various methods of image processing. Edge detection which is one of those is technique to detect dramatically changing part of image brightness. Existing methods detect edge through mask which is composited by constant values. Because existing methods do not consider factor as location, direction of pixel in image, performance of edge detecting in insufficient. Therefore, an algorithm which is using variable vector for the variation of brightness in mask of $3{\times}3$ pixels is proposed.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.473-480
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• 2004

This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.568-574
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• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.872-898
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• 2007

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.493-494
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• 2006

SU-8 can be implemented as a mask for micro Abrasive Jet Machining (micro-AJM) process [1]. In this paper, we will evaluate the quality of micro grooving result on glass substrate by micro-AJM process which using SU-8 as a mask. It was evaluated on width and edge profile of the micro grooving. The result was having distortion compare with the master film used to pattern the SU-8 mask. The value of distortion with other properties which came along with it, such as depth and surface roughness, can be optimized in order to fabricate micro-channel for micro-fluidic application.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.201-205
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• 2004

The digital color image can be distorted by noise for a transmission or other elements of system. It happens to vague of a boundary side in the division of a color image object, especially, boundary side of an input color image is very important because it can be determined to the division and detection element in pattern recognition. Therefore it is boundary part In this paper, it detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is cal led a variable BBM. It is confirmed by simulation that the proposed algorithm can be got the batter result edge at the place of closing to each edges and having smoothly curved line.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.267-269
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• 2015

In the modern society, the images provide the most effective information in multi-devices and the edge includes important feature information in such images. This edge is used as an essential preconditioning process in several application fields and many studies have been carried out in order to obtain the excellent images. The methods of Sobel and Roberts which are generally known are simple to implement the images but bring more or less insufficient processing result. Thus, this paper proposed an edge detection algorithm using the area averaging of segmented mask in order to supplement the problems of the current methods and compared it with such current methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.91-98
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• 2005

In this paper, we propose a temporal error concealment method based on the edge adaptive masking. In the method, four regions around the corrupted block - top, bottom, left, and right - are defined and the edge features of the regions are extracted by applying an edge operator for each direction. The size of a mask for the boundary matching is determined by the edge information, which can be considered as a criterion to measure the activity of the boundary region. In other words, it is determined such that the size of the mask is proportional to the amount of edge-component extracted from each region in order to yield the higher reliability on boundary matching. This process is equivalent to applying weights depending on the edge features, which leads the improved motion vector. In experiments, it is verified that the proposed method outperforms the conventional methods in terms of image quality, and then its merits and demerits are discussed.

• Journal of IKEEE
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• v.19 no.1
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• pp.10-17
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• 2015

In this Paper, an efficient method of FPGA based design and implementation of Sobel Edge detector block using 3-Line buffers is presented. The FPGA provides the proper and sufficient hardware for image processing algorithms with flexibility to support Sobel edge detection algorithm. A pipe-lined method is used to implement the edge detector. The proposed Sobel edge detection operator is an model using of Finite State Machine(FSM) which executes a matrix mask operation to determine the level of edge intensity through different of pixels on an image. This approach is useful to improve the system performance by taking advantage of efficient look up tables, flip-flop resources on target device. The proposed Sobel detector using 3-line buffers is synthesized with Xilinx ISE 14.2 and implemented on Virtex II xc2vp-30-7-FF896 FPGA device. Using matlab, we show better PSNR performance of proposed design in terms of 3-Line buffers utilization.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.47-53
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• 2008

A new intra-field deinterlacing algorithm with edge direction vector (EDV) in the image block is introduced. This proposed filter is suitable to the region with high motion or scene change. We first introduce an EDV, which is computed by Sobel mask used edge map, so that filer resolution of the edge direction can be acquired. The proposed EDV oriented deinterlacing system operates by identifying small pixel variations in five orientations, $26.5^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$, and $153.5^{\circ}$. The EDV values work as inputs of Sobel mask and return edge direction degree and confidence parameters. Based on edge direction degree and confidence parameters the missing pixel is computed. The results of computer simulations demonstrate that the proposed method outperforms a number of intra-field deinterlacing methods in the literature.